Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation.
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2019-01-16
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Advancements in the cost and speed of next generation genetic sequencing have generated an explosion of clinical whole exome and whole genome testing. While this has led to increased identification of likely pathogenic mutations associated with genetic syndromes, it has also dramatically increased the number of incidentally found genetic variants of unknown significance (VUS). Determining the clinical significance of these variants is a major challenge for both scientists and clinicians. An approach to assist in determining the likelihood of pathogenicity is signal-to-noise analysis at the protein sequence level. This protocol describes a method for amino acid-level signal-to-noise analysis that leverages variant frequency at each amino acid position of the protein with known protein topology to identify areas of the primary sequence with elevated likelihood of pathologic variation (relative to population "background" variation). This method can identify amino acid residue location "hotspots" of high pathologic signal, which can be used to refine the diagnostic weight of VUSs such as those identified by next generation genetic testing.
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Jones, Edward G, and Andrew P Landstrom (2019). Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation. Journal of visualized experiments : JoVE, 2019(143). 10.3791/58907 Retrieved from https://hdl.handle.net/10161/20295.
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Andrew Paul Landstrom
Dr. Landstrom is a physician scientist who specializes in the care of children and young adults with arrhythmias, heritable cardiovascular diseases, and sudden unexplained death syndromes. As a clinician, he is trained in pediatric cardiology with a focus on arrhythmias and genetic diseases of the heart. He specializes in caring for patients with heritable arrhythmia (channelopathies) such as long QT syndrome, Brugada syndrome, catecholaminergic polymorphic ventricular tachycardia, and short QT syndrome. He also specializes in the evaluation of children following a cardiac arrest or after the sudden and unexplained death of a family member. He has expertise in cardiovascular genetics and uses it to identify individuals in a family who may be at risk of a disease, even if all clinical testing is negative. As a scientist, he is trained in genetics and cell biology. He runs a research lab exploring the genetic and molecular causes of arrhythmias, sudden unexplained death syndromes, and heart muscle disease (cardiomyopathies). He utilizes patient-derived induced pluripotent stem cells and genetic mouse models to identify the mechanisms of cardiovascular genetic disease with the goal of developing novel therapies.
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